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A Novel Random Forest-Based Model to Predicting Anticancer Peptides

عنوان مقاله: A Novel Random Forest-Based Model to Predicting Anticancer Peptides
شناسه ملی مقاله: IBIS09_067
منتشر شده در نهمین همایش بیوانفورماتیک ایران در سال 1398
مشخصات نویسندگان مقاله:

Farid Nasiri - Peptide Chemistry Laboratory, Institute of Biochemistry and Biophysics, University of Tehran
Fereshteh Fallah Atanaki - Laboratory of Biological Complex Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
Saman Behrouzi - Laboratory of Biological Complex Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
Mojtaba Bagheri - Peptide Chemistry Laboratory, Institute of Biochemistry and Biophysics, University of Tehran
Kaveh Kavousi - Laboratory of Biological Complex Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran

خلاصه مقاله:
According to the report by the international Agency for Rrecentesearch on Cancer (IARC) , approximately 18.6 million new cancer cases were estimated and the cancer is responsible for about 9.6 million deaths in 2018[1]. Additionally, because of the emergence of resistance to chemotherapeutic drugs or their non-selective activity, causingsevere side effects, current cancer therapies are less effective. In this regard, the discovery and development of novel anticancer agents are in urgent need. In between, in the recent decade, anticancer peptides (ACPs) are considered useful multifaceted molecules that may overwhelm the tumor chemical resistance and non-selectivetargeting of neoplastic-cells. the ACPs are positively charged sequences of short to medium size length of 5-30 amino acids and structurally diverse peptides of α-helices and β-sheets[2].

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1164326/